Mass spectrometry is an important tool for use in chemical analysis. One problem confronted in the field of mass spectrometry is that, over extended periods of time, mass spectrometers can experience sensitivity drift or mass discrimination drift, which is also referred to as instrument bias. Mass discrimination in a mass spectrometer may be described as the favorable or disfavorable transmission of ions of a particular mass-to-charge (m/z) relative to ions at other m/z values in the mass range of the instrument. In other words, mass discrimination drift describes mass dependent changes in transmission across the mass range of the instrument. In addition, the overall sensitivity of the analyzer may change independent of m/z, which may be attributed to a change in detector sensitivity. This shift is termed sensitivity drift.
In quantitative mass spectrometry, calibration of an instrument consists of constructing a quantitative model from standards that relates the response and concentrations of the individual components in a mixture to the spectral response of the mixture. Unfortunately, typical models constructed for quantitation do not perform well over extended periods of time without recalibrating the instrument to account for instrumental sensitivity drift or mass discrimination drift. Such instrument changes directly affect the relationship between the respective responses of the standards and their concentrations in the originally constructed model. Generally, these instrumental changes are corrected by generating a new calibration model that again relates the component response to concentration. For the analysis of multicomponent mixtures, total recalibration can be a costly and time-consuming process which removes the instrument from its intended application. Even for those cases where the instrument can be autocalibrated, other concerns frequently arise relating to cost, long term analyte stability, and the handling of potentially toxic analytical standards.
In addition to variations of mass transmission within a single instrument, another problem in mass spectrometry is the variation in instrument bias among different instruments. Such variation can cause the mass spectrum of the same compound obtained on different instruments to differ substantially in appearance. This variation does not allow for the transfer of the previously mentioned quantitative models between instruments because the transmission and bias across the mass range is unique to each individual instrument.
Library searching techniques are commonly employed to assist and expedite the identification of spectra from unknown compounds. Typical library searching techniques consist of matching or assimilating an unknown spectrum with entries in a spectral reference library. Compounds in the library that have similar spectra to the unknown can be tabulated according to a numerical similarity index generated by a search algorithm. The problem with these approaches is most spectral libraries are constructed using a variety of experimental conditions and instruments allowing for large differences between reference spectra for the same compounds. Using current searching techniques, the most reliable match of an unknown to an entry in the library is obtained by generating the unknown and the reference library spectra under as close to identical experimental conditions on the same instrument as possible. Such constraints are not always practical or feasible.
The practice of mass spectrometry would be improved by a method which reduces the time and costs associated with correcting for mass discrimination and sensitivity differences in full scan, limited mass range scan, and selected ion scan mass spectrometric data.